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Ting Shu
Publications
- 2024
- [j68]Ting Shu, Zhijie Pan, Zuohua Ding, Zhangqing Zu:
Resource scheduling optimization for industrial operating system using deep reinforcement learning and WOA algorithm. Expert Syst. Appl. 255: 124765 (2024) - [j67]Ting Shu, Zhanxiang He, Xuesong Yin, Zuohua Ding, Mengchu Zhou:
Model-based diversity-driven learn-to-rank test case prioritization. Expert Syst. Appl. 255: 124768 (2024) - 2023
- [j62]Ting Shu, Cuiping Wu, Zuohua Ding:
Boosting input data sequences generation for testing EFSM-specified systems using deep reinforcement learning. Inf. Softw. Technol. 155: 107114 (2023) - 2022
- [i2]Zhijie Pan, Ting Shu, Zuohua Ding:
PTSG: a test generation tool based on extended finite state machine. CoRR abs/2209.10255 (2022) - 2021
- [j47]Yechao Huang, Ting Shu, Zuohua Ding:
A Learn-to-Rank Method for Model-Based Regression Test Case Prioritization. IEEE Access 9: 16365-16382 (2021) - [j42]Ting Shu, Yechao Huang, Zuohua Ding, Jinsong Xia, Mingyue Jiang:
Generating feasible protocol test sequences from EFSM models using Monte Carlo tree search. Inf. Softw. Technol. 135: 106557 (2021) - 2020
- [j29]Adekunle Akinjobi Ajibode, Ting Shu, Zuohua Ding:
Evolving Suspiciousness Metrics From Hybrid Data Set for Boosting a Spectrum Based Fault Localization. IEEE Access 8: 198451-198467 (2020) - 2019
- [c7]Keke Du, Mingyue Jiang, Zuohua Ding, Hongyun Huang, Ting Shu:
Metamorphic Testing in Fault Localization of Model Transformations. SOFL+MSVL 2019: 299-314 - [c6]Baoyi Pan, Ting Shu, Jinsong Xia, Zuohua Ding, Mingyue Jiang:
A Fault Localization Method Based on Dynamic Failed Execution Blocks. SOFL+MSVL 2019: 315-327 - 2016
- [j9]Ting Shu, Tiantian Ye, Zuohua Ding, Jinsong Xia:
Fault localization based on statement frequency. Inf. Sci. 360: 43-56 (2016) - [j8]Ting Shu, Zuohua Ding, Mei-Hwa Chen, Jinsong Xia:
A heuristic transition executability analysis method for generating EFSM-specified protocol test sequences. Inf. Sci. 370-371: 63-78 (2016)
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last updated on 2024-09-13 01:39 CEST by the dblp team
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